Mike Lindow

(He/Him) With a strong analytics background and academic research experience, I’m pursuing a career as a computational social scientist focusing on publication. Inspired by my advisors’ consumer behavior background, I apply machine learning and econometric methods to further study consumer interactions as the first Computational Marketing emphasis in the David Eccles School of Business. 

I act as a bridge between modern data-driven tools and daily decision-making. In the information age, repeated stored social interactions now allow us as a network of communities to reflect on ourselves and our communal values. I'm interested in the deeply embedded social values that appear through applying computer-driven methods to behavioral outcomes.

I mostly study consumer behavior, human performance optimization, machine learning, natural language processing, econometrics, algorithmic fairness, the economics of AI, prediction explainability, and analytics education and accessibility.

I currently work with the Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF) as a bioinformatics researcher, leveraging medical and military repositories to predict behavioral outcomes. I collaborate with military clinicians within the Defense Health Agency (DHA) and the amazing researchers and investigators within the Consortium for Health and Military Performance (CHAMP).